Application of Rough Set and Adaptive Genetic Algorithm to Transformer Fault Diagnosis
Jun Rao · Electrical Measurement & Instrumentation · 2012
A method of genetic algorithm combined with rough set is proposed in this paper for attribute reduction of the decision table for power transformers' fault diagnosis,and a modified method of value reduction is adopted to obtain the minimal decision table.Besides,the fault diagnosis rules are extracted from the final reduced decision table.Pretreatment of initial population,the method of preserving optimal L individuals,and the method of parents-with-only-child are introduced to accelerate the convergence rate of the algorithm.Lastly the validity and the feasibility of the derivative rules are illustrated by two examples.The algorithm is simple and fast and can be applied into the fault diagnosis of power transformers efficiently.